In this paper we instead applied Bayesian reasoning to define probabilities. The advantage of this approach is first and foremost a practical one. All attempts to define
a semi-classical measure rely on certain assumptions. The Bayesian framework naturally compels one to make all assumptions explicit through prior information.
Our approach has been strongly influenced by Jaynes' view of probability theory as an extension of classical logic [1]}. Probabilities, in this viewpoint, amount to reasonable
expectations [2]} drawn from limited information. Our treatment is also inspired by Caves' elegant resolution [3]} to the Doomsday argument [4]}, [5]}, [6]}.
Our approach does not rely on ad hoc geometric constructions, nor are we counting anything.
